Summer's here, but we've been locked inside stress-testing AI prompts so you don't have to.
Every month, our team digs through the internet's prompt goldmine—testing the genius, the bizarre, and the surprisingly effective. This is your monthly shortcut, an insider's guide to the prompting strategies that actually move the needle (and the epic fails that taught us what not to do).
This isn't your typical "10 ChatGPT Tips" clickbait. These are real prompt experiments we've run, refined, and occasionally regretted trying in front of our bosses. From teaching Claude to write like your favorite author to making Gemini stop hallucinating random facts, July's tips are loaded with game-changers.
🧠 Missed June 2025's Prompt Tips? Catch up here →
🧠 Missed May 2025's Prompt Tips? Catch up here →
🧠 Missed April 2025's Prompt Tips? Catch up here →
Pro tip: Don't just skim and scroll. Save this page. Some of these prompts might sound weird (yes, we're talking about the "AI therapist for your spreadsheets" technique), but they could completely transform your AI workflow.
Grab your iced coffee, fire up your favorite AI tool, and get ready to level up your prompting game. July's tips are here—and they're scorching hot.
July 1
Phil Scmid wrote a great blog breaking down “context engineering” and what it means beyond your typical prompt. The TL;DR = It's about building systems that give AI all the right information, tools, and format at the right time.
Think of context as everything your AI sees: instructions, conversation history, retrieved documents, available tools, even output format requirements.
Credit: Phil Schmid
Phil's example shows the difference between a “cheap demo” agent that only sees a basic request, versus a “magical” agent that has access to your calendar, past emails, contact info, and scheduling tools.
Instead of a robotic “What time works for you?” response, you get: “Tomorrow's packed on my end, back-to-back all day. Thursday AM free if that works? Sent an invite, lmk if it works.”
The magic isn't in the prompt. It's in the prep work that makes the prompt unnecessary.
Here’s how to put this practice: Before you prompt “help me schedule a meeting,” first gather your calendar, the other person's availability preferences, and past meeting patterns, then let the AI suggest optimal times. Try using a tool like n8n or OpenAI’s new connectors system to pool this data all in one place for your AI to access.
July 2
It’s time to level up your AI use in 2025, and we’ve got three videos to help you do it!
- Jeff Su shares how (and when) to use ChatGPT’s web search, Deep Research, and Canvas tools work.
- Tina Huang top tools for how to use AI in your daily life, including her top chatbot picks, her top agent tools, and her top vibe-coding tools, and how she uses them across both work productivity and daily life stuff.
- Grace Leung’s tutorial shares her simple 3-step framework for building a scalable AI work team, including how to map your workflow, design specialized AI assistants, put together an AI research team, and add a manager agent to delegate tasks between your research and visual agents.
You can watch all three videos in only ~40 minutes. Come on, you got 40 minutes to spare… think of all the time watching these will save you once you learn all their secrets!
July 3
Following Dylan Patel’s advice, if you’re trying to get insights into why such and such topic is trending on X.com, you can use Grok to give you real time insights (which is useful for tracking current events, even if you don’t use the platform X or the AI Grok).
Try something like this:
Why is [topic] trending on X right now [today’s date]? Search X for the latest discussions about [topic] to confirm. Only return X posts from today, [today’s date] related to this topic please.
Sometimes Grok is hit or miss, so I’d try this with Grok’s “DeepSearch” tool. It might not give you the exact X posts every time, but it can pull in additional context to help explain why a given topic might be trending given recent news events.
Now, if you try this prompt with ChatGPT using a thinking model like o3, it can also search X.com (when we tried this with Perplexity’s “social search” feature, it failed). So if you prefer ChatGPT over Grok, that’s another way to get insights into trending news.
July 7
Here's a micro-adjustment that makes your AI way more responsive: instead of telling your AI what NOT to do, like saying “don't do X”, turn the negative framing (“don’t”) into a positive framing, like: “avoid.”
So instead of “don't use jargon,” try “avoid jargon.” Instead of “don't be wordy,” say “avoid being wordy” or even better, “be concise.” It's the same instruction, just reframed in a way that the AI’s training responds to better.
Remember: It's not about going fully positive. Sometimes you need to give negative instructions. The trick is reframing the instruction into a positive action the Ai can act on. This is not unlike directing actors… giving the AI a positive verb to “act” on.
July 8
Want to make better use of meeting time? Rather than having AI summarize meetings you skip, Ethan Mollick suggests you use it to make the meetings you attend actually worth attending.
He shared this prompt to facilitate better meetings that generates custom “tarot cards” with questions to rescue your stuck meetings.
He says to feed Claude your meeting transcript halfway through with this prompt, and it’ll create 5-6 targeted questions like “What pattern keeps bringing us back to this topic?” to actually make progress on your most important topics.
Instead of endless circles, you get focused breakthrough questions that actually move conversations forward.
July 9
Balaji shared a prompt tip that could save you thousands on consulting fees. He suggests you can turn any professional into an AI fact-checker.
Here's the hack: First, prompt your AI to become the best lawyer/accountant/doctor in your city, then write a detailed memo about your situation with specific questions (don't forget to ask “what am I overlooking?”).
Run this same prompt across multiple AIs: ChatGPT, Claude, Gemini. Then, organize their answers in a spreadsheet.
Now, you've got a comprehensive survey of expert opinions, complete with citations and draft documents. Now take this research doc to the actual human professional and ask them to verify the AI's work.
The result? You're no longer paying billable hours for basic education. Instead, you're paying for expert verification and final polish; exactly what professionals should be doing.
Our favorite insight: This works with any expert, from doctors to accountants. AI handles the “middle-to-middle” work, while humans do what they do best: verify accuracy and add final expertise.
July 10
Try out the CRIT method from Geoff Woods in your next prompt (found on Reddit):
“CONTEXT: Give as much information as you can about the situation; what you know, what you don't know.
ROLE: Give the assistant a specialized role to work from (who or what you want it to be).
INTERVIEW: Have it ask you 1 question at a time (usually 5-7, but whatever number you think is appropriate) to gain deeper context.
TASK: Whatever you want the assistant to do.”
The interview tip seems like the one that’s the most useful. It’s kinda like when Deep Research asks you a series of follow up questions before it begins. Very useful tip!
July 11
Stop wasting time re-prompting the same tasks over and over. Here's the hack that changed our workflow:
The first AI response to your prompt is usually the smartest (the longer the chat, the harder it is for the AI to “focus”), but iteration helps you provide feedback to the AI to get what you truly want.
After you've iterated your way to the perfect AI output, ask the AI: “Now, write me a single prompt that would provide the exact same output in one shot.”
Then, save THAT prompt in as the custom instructions in a project for instant reuse (name the project after the task the prompt accomplishes).
This turns your projects into a personal prompt library, while also teaching you better prompting skills (“ohhh, so THAT’S what I should have said).
July 14
Yesterday, a confused Redditor posted one of those overwhelming “ChatGPT Prompting Cheat Sheets” filled with acronyms like R-A-I-N and F-L-O-W and asked for help. The community's advice? Ditch the acronyms and frameworks.
The top-voted response: “Using ChatGPT comes down to literally just talking. That's it.”
So while all of this advice WILL help you create better prompts, this is a good reminder that a lot of time, it's more important to provide the MOST CONTEXT possible than format things according to any specific structure.
As an example, try this next time you have a prompt problem: Instead of complex prompts, try simplifying things: “I need help writing a cover letter. I'm applying for marketing roles and have strong social media experience. Here is my full resume (remove any personally identifying info, just copy your roles / experience)" and then give it all the context about what you’ve done and what the roles you’re applying for require, and let it cook.
This is where “context engineering” comes in: in order for your AI to be successful, you need to give it the maximum amount of context possible (see above). A lot of times, that involves using Claude or ChatGPT Connectors, which connect external data sources and tools to your AI. But in a simple chat window, context engineering would be connecting all of the information the AI needs to do the job completely (in this example: your resume, job description, company info, and anything else that could help you stand out, like why you want this job or why you personally think you're qualified for it).
Then, when you get a response, give it feedback on what you like and don’t like or what still needs work. And truly, for most things, that’s all that’s needed.
We finally made it easy to talk to computers with natural language… so why are we overcomplicating things by talking like robots again?!
P.S: this doesn't invalidate any of the other prompt advice. But these models are getting so smart, you can usually get away with just providing lots of context in your prompt for one-off tasks and get a good enough response.
The counter-factual to this is: the more formulaic and mission-critical the task is, the more you want strict guidelines and rules to guide the prompt. So for example, if you're running an AI in a production workflow, you want to highly tune your prompt with proper markdown formatting and rigid structure.
July 15
Ethan Mollick recently warned that AI’s sycophancy problem goes beyond flattering your intelligence; models will actually abandon correct facts just to agree with you. Even asking “Are you sure?” can flip a right answer to wrong.
To adjust for these issues, you could try the OPEN approach:
- Open-ended questions (Ask “What is best” not “Why is X best?”).
- Premise-free framing (avoid embedded assumptions).
- Evidence requests (ask for sources/data).
- Neutral language (remove certainty markers).
To apply the above, try this Meta-prompt hack: Ask AI to rewrite your prompts for truth-seeking:
“Please rewrite my question to be more neutral and unbiased. Remove any embedded assumptions, leading language, or repeated terms that might bias the response. Transform it into an open-ended query that encourages critical analysis and considers multiple perspectives, like a scientist testing a hypothesis. My original question: [your question here]”
July 16
Today we’re going to cover two simple requests you can include in your prompts to encourage your thinking AI models to think hard.
For starters, try adding “ultra think” and “think ultra hard” in your prompts (this is advice from Kieran Klaassen, via Peter Yang).
The AI creators have suggested that using terms like “give it all you got” and “think hard” help encourage the model to really think on something (they also have “thinking budgets” you can edit in the API).
The second idea is to use “really think. Really, really think.” That’s from Matt Shumer, who shared this prompt on X that helps for UX/product design.
Try them both, see if it helps!
July 17
Here are 15 core techniques to get better AI outputs from Anthropic:
- Be clear and specific - state task upfront, provide context.
- Use examples - show the format/style you want.
- Encourage thinking - ask Claude to "think step-by-step."
- Iterative refinement - give specific feedback for improvements.
- Leverage Claude's knowledge - include relevant context.
- Use role-playing - "As a senior marketing consultant..."
- Specify your audience - tell Claude who content is for.
- Define tone and style - describe desired voice.
- Define output structure - provide outlines/lists to cover.
- Be specific about summaries - ask for specific aspects.
- Use document names - refer to attachments by name (ex:
